Details
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Improvement
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Status: Resolved
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Minor
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Resolution: Incomplete
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2.0.0
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None
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Linux, Scala but probably general
Description
When awaitTermination propagates an exception that was thrown in processing a batch, the StreamingContext keeps running. Perhaps this is by design, but I don't see any mention of it in the API docs or the streaming programming guide. It's not clear what idiom should be used to block the thread until the context HAS been stopped in a situation where stream processing is throwing lots of exceptions.
For example, in the following, streaming takes the full 30 seconds to terminate. My hope in asking this is to improve my own understanding and perhaps inspire documentation improvements. I'm not filing a bug because it's not clear to me whether this is working as intended.
val conf = new SparkConf().setAppName("ExceptionPropagation").setMaster("local[4]") val sc = new SparkContext(conf) // streams will produce data every second val ssc = new StreamingContext(sc, Seconds(1)) val qm = new QueueMaker(sc, ssc) // create the stream val stream = // create some stream // register for data stream .map(x => { throw new SomeException("something"); x} ) .foreachRDD(r => println("*** count = " + r.count())) // start streaming ssc.start() new Thread("Delayed Termination") { override def run() { Thread.sleep(30000) ssc.stop() } }.start() println("*** producing data") // start producing data qm.populateQueue() try { ssc.awaitTermination() println("*** streaming terminated") } catch { case e: Exception => { println("*** streaming exception caught in monitor thread") } } // if the above goes down the exception path, there seems no // good way to block here until the streaming context is stopped println("*** done")